Method for generating a medical network

ABSTRACT

A method for setting up a medical network for carrying out at least one medical function is disclosed. The medical network comprises network nodes and the network nodes are set up for communicating with one another by an initialization step, wherein the network nodes exchange initialization information that includes information characterizing the network nodes and a self-organization step where the network nodes define their role distribution. A work step where the network carries out the medical function and the two network nodes interact in the role of distribution defined in the self-organization step.

REFERENCE

This application is a continuation of U.S. application Ser. No.13/658,310 filed 23 Oct. 2012, which is a continuation ofPCT/EP2011/056336 filed 20 Apr. 2011 which is based on and claimspriority to European Patent Application No. EP 10160904.8 filed 23 Apr.2010, which are hereby incorporated by reference.

FIELD

The invention relates to a method for setting up a medical network forcarrying out at least one medical function. Medical networks of thistype may be used in the context of self-organizing near-bodycommunication systems.

By way of example, networks of this type can be used to care forpatients having chronic illnesses and/or high-risk patients, a pluralityof whose body functions have to be monitored and/or influencedsimultaneously. However, other fields of use are also conceivable.

BACKGROUND

Both in the clinical sector and in private health care, there is a needfor systems and networks which are able to monitor the complex interplayof individual body functions of a patient and, if appropriate, toinfluence body functions in a targeted manner. By way of example, thiscan involve care of chronically ill patients, such as diabetes patients,for example. High-risk patients can also be cared for in this way, forexample high-risk patients who are known to be at increased risk ofinfarct. Generally, it should be pointed out that the term “patient”used in the context of the present invention does not necessarilyrestrict the target group circle to ill human or animal patients,however, rather that, in principle, healthy target groups can also becared for by means of the devices proposed below. Generally, therefore,the term “patient” can be at least substantially equated with the term“user”.

In many cases, the communication between the individual components ofthe system presents a challenge in complex medical systems. Medicalcommunication systems are known from various prior art documents. By wayof example U.S. Pat. No. 7,161,484 B2 describes a system for monitoringmedical parameters of a patient comprising at least one sensor fordetecting at least one predetermined medical parameter. Furthermore, atransmission means for transmitting the medical parameters detected bythe sensor is provided, wherein the transmission is sent to a remotelyarranged server. U.S. Pat. No. 7,163,511 B1 describes a device and amethod for frequently measuring the concentration of an analyte in abiological system. In this case, use is made of a monitoring systemcomprising at least two components in order to facilitate the datacollection and the displaying of the data. In US 2007/0027367 A1, apersonal area network for receiving, storing, processing, displaying andcommunicating physiological data is disclosed, which uses an openarchitecture and which may comprise a personal server, such as acellular phone. The open architecture allows additional sensors to jointhe network, without rendering the personal server irrelevant.

Wireless communication in relatively close proximity to patients takesplace nowadays predominantly by means of radio systems which utilize theentire electromagnetic field and usually operate in the far field. Inthe case of far field communication, the distance between a receiver anda transmitter antenna is greater than double the wavelength of the radiocarrier frequency chosen. At 2.45 GHz, this is approximately 0.3 m.Diverse radio technologies are standardized under IEEE 802.11 andrelated standards. In this case, principal features are that an ISMfrequency (Industry Science Medical, for example 2.45 GHz) is used andthat with a limited transmission power of approximately 100 mW, forexample, distances of approximately 1-10 m are bridged. ISM frequenciesare generally accessible frequency bands, i.e. frequency bands notallocated by organizations or governments in accordance with strictrules. The only ISM frequency band that can currently be used withoutrestrictions throughout the world whilst observing the presentlyapplicable standards is the 2.45 GHz band.

Furthermore, systems are available that use only the magnetic fieldcomponent. Only distances within the antenna near field can thereby bebridged, owing to physical conditions. Such systems are in use as RFIDsystems (Radio Frequency Identification, also called Transponders) or asNFC systems (Near Field Communication). RFID systems are distinguishedby the fact that a so-called reader induces data and energy in aso-called transponder. The transponder modifies the data, ifappropriate, and returns them to the reader again. The transponder isgenerally only active if it is situated in the influencing field of theenergy of the reader. NFC works using the same structures and protocolsas RFID, but in this case the transponder also comprises its own energysource, such that only the communication is activated by the reader, butthe application can remain active even outside the influence of thereader. This is advantageous particularly in the case of distributed,continuously measuring sensor systems.

Communication systems which utilize only the electric field component ofthe electromagnetic field have also been known for some time. Owing tothe breakdown strength of air, which is approximately 1000 V/mm, theelectric field component can transmit at most only approximately 1/90000of the energy of the magnetic field (See e.g. K. Küpfmüller et al.:Theoretische Elektrotechnik: Eine Einführung, 10. Auflage, SpringerVerlag, Berlin, S. 333. Therefore, the remote action component is inmany cases limited to a direct touching contact.

However, it has been found here that a human body is relatively wellsuited to conducting dielectric displacement currents. The transmissionof items of information is therefore possible without the latter leavingthe conducting body over a wide area. Such networks which operate in thenear-field range and utilize the human body for transmitting signals areknown, in particular, in the field of applications for personalinformation and communication, for example from U.S. Pat. No. 6,542,717B1, from T. G. Zimmerman: “Personal Area Networks (PAN): Near-FieldIntra-Body Communication”, master's thesis at the MassachusettsInstitute of Technology, September 1995, or from M. S. Wegmüller:“Intra-Body Communication for Biomedical Sensor Networks”, dissertation,ETH Zurich, 2007, where such networks are also referred to as PAN(Personal Area Network). Such networks use electric fields as acommunication medium between transmitters which are arranged on persons.

Systems which utilize the human body for communicating signals are alsoknown from the medical sector. Thus, U.S. Pat. No. 6,315,719 B1, forexample, describes a system which can be used for long-term medicalmonitoring of a patient, for example an astronaut. In that case, anautonomous sensor unit is arranged on a person's body, said sensor unithaving electrodes. These electrodes are arranged on the skin by means ofan adhesive strip. Furthermore, a transmitter and receiver worn on thebody is provided, which serves as a central unit.

In the field of diabetes diagnostics, in particular, previousdevelopments have generally concentrated on the detection of a smallnumber of individual parameters with direct diagnostic reference. By wayof example, glucose from arterial blood or from the interstitium ismeasured. In this case, a treating physician is generally consulted as acontrol entity. Said physician also defines the therapeutic measures.Further diagnostic measurement variables or else personal experience andknowledge-based rules are included in this case.

As a result of the development of sensor technology, extended in-vivodiagnostics have become possible nowadays, for example as a result ofthe possibility of continuously measuring glucose concentrations. As aresult of further miniaturization, the detection of various parametersin the blood, for example electrolytes, blood gases, chemical parametersor the like, stress parameters (for example diverse hormones), but alsophysio-physical parameters (e.g. blood pressure, heart rate, fatcontent, weight, temperature), becomes possible instantaneously orcontinuously. Such a system is described in WO 2004/039256 A2, forexample.

Over and above these physically and/or chemically measurable variables,diagnosis and therapy are in many cases also influenced by personalfactors such as well-being, stress and external influences such as, forexample, the weather, time changes or the like, but also events such aseating, periods of sleep, sport or the like. Examples of systems whichtake account of such factors are described in US 2007/0238934 A1 or inUS 2009/0131759 A1. From an overall assessment of the diagnostic values,therapy plans can then be created and implemented.

Suitable actuators make it possible nowadays to a limited extent toimplement said therapy plans automatically, in a temporally coordinatedmanner. Examples of such actuators are an insulin pump, a medicamentdispenser, triggering of physiological stimuli or the like.

Diagnostic systems of the type described above therefore consist ofnumerous complex individual modules with differing handling, start-up,calibration or similar requirements. Precisely in the field of patientself-diagnostics, therefore, it is often the case that simple and hencefault-tolerant start-up and control of the systems and subsystems by theuser still do not exist. The construction of diagnostic systems andnetworks is additionally made more difficult by lack of interoperabilityor a complicated method of identification and assignment of systemcomponents. It is often necessary to manually input long series ofnumbers, parameters or items of time information, which can lead to asusceptibility of the systems to faults. Moreover, owing to hithertosubstantially lacking sensor technology, the inclusion of extracorporealevents, such as eating, sleeping, sport or stress, for example, isgenerally possible only by manual inputting by the person respectivelyconcerned. This may be associated with the corresponding inputtingerrors and also errors in the time reference. If a correct temporalassignment is not provided, this can give rise to large diagnosticerrors, and the latter in turn to therapy errors.

If a plurality of sensors and/or actuators are intended to be combinedto form a common system and are networked, then it is furthermore almostno longer possible for the layperson to coordinate these systems.Operating errors with serious consequences should be expected.

In WO 2007/096810 A1, a body area network (“BAN”) is disclosed,comprising a plurality of devices, each device comprising means fordetecting other similar communication devices. A method for setting upthe BAN is disclosed, wherein a first sensor device is switched on andsearches for other sensor devices by using a request. Since it is thefirst sensor device, there is no other sensor device responding to therequest, and first sensor device is switched to a wait mode. Once asecond sensor device is added and switched on, the second sensor devicesends a request, which is answered by the first sensor by creating aBAN. The first sensor and a RF device included by this first sensorautomatically takes over the role of the coordinator of the BAN.

The setup and method disclosed by WO 2007/096810 A1, however, has somesignificant shortcomings. Firstly, the role distribution of the setup isfixed in an arbitrary way in that the device, which accidentally isattached to the body first, automatically takes over the role of thecoordinator of the network, independent from its physical nature, itshardware and software resources and independent from its requirements interms of the type of data generated by the device. Since the roles inthis network are pre-determined, a situation might easily occur in whichthe device least suitable for being the coordinator takes over thiscoordinator role of the network.

Similarly, EP 1 676 525 A1 discloses a medical device communicationsnetwork comprising a plurality of medical devices having wirelesscommunication circuits. A master wireless communications circuit may becomprised, which may receive medical device information from a pluralityof slave wireless communication circuits. The devices exchange deviceidentification codes. The network is set up to thereby monitor thatappropriate instruments are matched with appropriate devices.

WO 2008/015627 A1 discloses a system comprising a plurality of networkcomponents and a network management device. The components are adaptedto communicate by wireless short-range communication. The networkmanagement device comprises a body-coupled communication interface andis adapted to configure the plurality of network components by means ofthe interfaces to form a network and to avoid conflicts between thenetwork components.

Again, as in WO 2007/096810 A1, the networks disclosed by EP 1 676 525A1 and by WO 2008/015627 A1 have the technical shortcoming that theroles of the network devices are predetermined. Thus, in case there is amaster device or management device, the role of this device as a networkmaster is known from the beginning and remains unchanged duringoperation of the network. The network does not exhibit any flexibilityregarding the fact that other devices may be added which might be moresuited for taking over the role of the master device. Further, the fixedrole-distribution generally is unable to react to changing needs andrequirements within the network, such as to a situation in which anetwork node is added which requires a more time-critical data handlingor which requires a modification of the allocation of hardware resourceswithin the network.

SUMMARY

A method for setting up a medical network which at least substantiallyavoids the disadvantages of known systems and networks is provided. Inparticular, the method is intended to enable even complex networkscomprising numerous network nodes to be set up by a layperson who is notmedically and technically trained. Further, the method is intended toexhibit a high flexibility with regard to network components actuallycomprised by the network and the specific requirements, and with regardto changing compositions, needs and tasks of the network.

Accordingly, a method for setting up a medical network for carrying outat least one medical function is proposed. In this case, setting up canbe understood to mean, in principle, creating, in particular producing,a new network. As an alternative or in addition, however, setting up canalso be understood to mean reconfiguration of an already existingnetwork, for example by one or a plurality of new network nodes beingadded to an existing network, by a new function being added to anexisting network, by one or a plurality of network nodes being removedfrom an already existing network, or the like. Once again as analternative or in addition, the term setting up can also encompassoperation or part of operation of the medical network since, as will beexplained in greater detail below, during operation, too, optimizationof the network or improvement of the interaction of a plurality ofnetwork nodes can be effected, which shall also be subsumed under theterm setting up the network.

In this case, in the context of the present invention, a network shouldbe understood to mean a device comprising at least two, and possiblythree, four or more, network nodes. The network nodes respectivelycomprise at least one device which is set up for carrying out at leastone node function. Examples of such functions are explained in greaterdetail below. The network nodes can be physically connected to oneanother. All or at least two, three or more of the network nodes are setup for communicating with one another in a wireless or wire-basedfashion.

The medical network can be, in particular, a near-body network, that isto say a network in which one, two or more of the network nodes arearranged on, in or in direct proximity to a body of the user, such thatsaid network nodes, on account of the proximity to the body, are set up,for example, for detecting at least one parameter of the body and/or forinfluencing at least one body function and/or for communication via thebody and/or for carrying out similar functions for which spatialproximity to a body of a user is required. By way of example, at leastone, and possibly two, three or more, of the nodes can be arranged at adistance of not further than one meter from the surface of a body of theuser, such as not more than 50 cm and particularly preferably not morethan 10 cm from the body of the user, during the operation of themedical network, or, alternatively or additionally, into the body of theuser, e.g. by way of implantation into the skin.

The network nodes are set up for communication with one another. Thismeans that at least two of the network nodes are set up forcommunication with one another, such as a plurality of the networknodes, and in particular all of the network nodes. The communication canbe configured in each case in a unidirectional or bidirectional fashion.As explained above, the communication can be provided for example in awireless fashion, in a wire-based fashion or else in a mannerincorporating the body of the user.

The method for setting up the medical network comprises at least thesteps presented below. The steps presented can preferably be carried outin the order presented. However, in principle, the steps can also becarried out in a different order, in a temporally overlapping fashion oreven temporally in parallel. By way of example, parts of the network canalready undergo transition to a subsequent method step, for example thework step, while other parts of the network are still in a precedingstep of the method, for example in an initialization step orself-organization step. The steps of the method are therefore intendedto relate at least to part of the network, that is to say at least twoof the network nodes. Other network nodes can be excluded from themethod. Furthermore, it is pointed out that the term method step caninclude a short duration of this step, but that a more lengthyimplementation of the steps is also possible. Accordingly, individual ora plurality of the method steps described below can also be configuredas a “phase” of the method and be implemented in a lengthier fashion. Byway of example, the network can be set up for effecting the medicalfunction of the network over a duration of a number of minutes, a numberof hours or even a number of days, for example seven days or more, forexample in the work step described below. A longer duration of theself-organization step and/or of the initialization step and/or repeatedimplementation of one or both of these steps is also conceivable, inprinciple, as is repeated implementation of the work step describedbelow.

The method proposed comprises at least one initialization step. In thiscase, an initialization step should be understood to mean a step inwhich at least two of the network nodes exchange at least one item ofinitialization information. This exchange can be effected in aunidirectional or else once again bidirectional fashion. In this case,the initialization information is intended to comprise at least one itemof information characterizing the network nodes which are involved inthe initialization step, or at least one of said network nodes,preferably at least two of said network nodes. The initializationinformation therefore makes it possible for at least one of the networknodes to set itself, part of the entire network or the entire networkwith regard to the particular features of the network node whoseinformation is contained in the characterizing information. Theinitialization step can take place in particular according topredetermined rules, in particular deterministically, for exampleaccording to a predetermined protocol. However, other configurations arealso possible, in principle.

Furthermore, the method comprises at least one self-organization step,which can be carried out after the conclusion of the initializationstep. A temporal overlap with the initialization step is alsoconceivable, but the self-organization step can begin after theinitialization step. In the self-organization step, the network nodes,that is to say, for example, two, three, several or even all of thenetwork nodes of the medical network, define a role distribution of thenetwork. Said role distribution can relate to different aspects of asubsequent interaction for carrying out the at least one medicalfunction, for example division of the resources, reciprocal control,communication among one another or communication with at least oneelement outside the medical network, or the like. Examples will beexplained in greater detail below.

Furthermore, at least one work step is carried out. The at least onework step can be carried out after the initialization step has beencarried out and/or after the self-organization step has been carriedout, or after the beginning of one or both of these work steps. Since,as explained above, parts of the network can carry out the method stepsat different points in time, or since only parts of the network may beinvolved in carrying out the method, other parts of the network may,however, also already commence the work step while further parts of thenetwork are still in the initialization step and/or in theself-organization step. In the work step, the network carries out the atleast one medical function. When carrying out this at least one medicalfunction, at least two of the network nodes interact in accordance withthe role distribution defined in the self-organization step.

The method according to embodiment of the invention overcomes theabove-mentioned shortcomings of the methods and networks known from theprior art. Thus, in contrast to the method disclosed by WO 2007/096810A1 which simply discloses the transmission of a “wakeup” call once a newsensor is added to the network, the present invention comprises the atleast one initialization step in which the at least one item ofinformation characterizing the network nodes is exchanged. In contrastto the predetermined role distribution as disclosed by WO 2007/096810A1, by EP 1 676 525 A1 and by WO 2008/015627 A1, the method of thepresent invention further comprises the self-organization step in whichthe role-distribution of the network nodes is defined. The item ofinformation characterizing the network nodes, as exchanged during theinitialization step, may form a solid basis for the self-organizationstep.

Thus, the role distribution may be defined by making use of thisinformation characterizing the network nodes, such as by attributing theroles to the network nodes which are most suited for the specific role.Thus, the at least one item of information characterizing the networknodes may be compared. This comparison, which may be part of theself-organization step and/or of one or more other steps, may beperformed by one or more of the network nodes. Thus, the method cancomprise at least one comparison of the at least one item of informationcharacterizing the network nodes, wherein the definition of the roledistribution of the network nodes may at least partly be based on aresult of this comparison. In this comparison, the present situation ofthe network may be analyzed, including an analysis of hardware and/orsoftware resources available and/or an analysis of requirements andneeds, as well as an optional analysis of the one or more medicalfunctions to be performed in the work step.

As an example, the self-organization step may be carried out in such away that the role distribution comprises a determination of at least onenetwork node as master node and a determination of at least one networknode as slave node. One or more network nodes may be capable of takingover the role of the at least one master node. The master node may beadapted to control one or more functions of the slave node. Thisdetermination might be adapted to change during operation of thenetwork, e.g. in reaction to a change in composition of the networkand/or in reaction to a change in one or more of the medical functionsto be performed by the network. As outlined above, the determination maymake use of the at least one item of information characterizing thenetwork nodes and may be based on a comparison of this at least one itemof information. Thus, the network node having the most powerful hardwareresources may be defined as the master node. The term most powerfulhardware resources may refer to the fact that the master node may bechosen such that the master node has a computing device, such as amicrocontroller, having the highest frequency amongst all network nodes.Alternatively or additionally, the master node may be the network nodehaving the highest data storage capability amongst all network nodes.Again alternatively or additionally, the network node having the mostpowerful and/or the fastest communication capabilities may be defined asthe master node.

Alternatively or additionally, the definition of the roles may be basedon one or more functions to be performed by the nodes, such as by the atleast one medical function. The at least one item of informationcharacterizing the network nodes may comprise information regarding thisat least one function, and, thus, the comparison discussed above maycomprise a comparison of the functions and/or of the needs of thenetwork nodes and/or a comparison of the hardware and/or softwarerequirements and/or a comparison of the sensitivity of the functions.The latter can e.g. comprise a comparison of the need of speed for datatransmission. Thus, generally, the network node having the most timecritical function may be defined as the master node. Herein,time-critical may refer to the fact that the function to be performed bythe master node may imply the need for the fastest transmission and/orreceiving of data and/or control commands amongst all network nodes.This may e.g. be the case for medical functions such as sensorfunctions, which might generate abnormal results requiring immediateattention by a user and/or a doctor. Thus, alternatively or additionallyto the possibilities listed above, the network node having the mostsensitive medical function and/or having the most time-critical datatransmission requirements may be chosen as the master node.

Other roles besides master and slave roles are possible. Thus, one ormore network nodes can take over the role of a storage device for themedical network and/or for a part of the medical network, such as one ormore network nodes having the highest data storage capability.Similarly, one or more network nodes can take over the role of acommunicator with one or more devices outside the medical network. Thus,this communicator role can be taken by one or more network nodes havingthe highest and/or fastest data transmission capability.

Other possibilities regarding the role distribution are feasible.Optionally, the at least one self-organization step can be performedrepeatedly, such as to keep the role distribution flexible duringoperation of the medical network. Thus, the role distribution can beadapted to changing functions to be performed by the medical networkand/or to a change in composition of the network, such as by addingand/or removing one or more network nodes. Generally, the method may beadapted to change the role distribution of the network nodes duringoperation of the medical network.

In the context of embodiment of the invention, the term medical shouldgenerally be understood to mean identification of body states and/ordetection of specific parameters of a body of a user, in particular adiagnostic property, and/or influencing the body of the user in anydesired fashion, in principle, for example by exerting at least onephysical and/or chemical and/or biological and/or environmentallygoverned stimulus. Accordingly, a medical function of the network is afunction which yields at least one medical result and/or yields at leastone medical stimulus or medical influencing within the meaning of theabove definition of medical. In particular, the medical function of thenetwork can comprise at least one of the following functions: a sensorfunction for detecting at least one measurement variable of a body, of auser, in particular a diagnostic function. This can be, in principle,any function in which at least one body state, at least onephysiological parameter or other variable characterizing a state of abody of a user is detected. Examples that shall be mentioned hereinclude continuous or discontinuous measurement and/or qualitative orquantitative detection of one or a plurality of analytes, for exampledetection of glucose in one or a plurality of body fluids, detection ofvarious parameters in the blood such as, for example, electrolytes,blood gases, chemical parameters, detection of stress parameters (forexample by detecting one or a plurality of hormones), detection ofphysio-physical parameters such as, for example, blood pressure, heartrate, fat content, weight, temperature, or a combination of the statedand/or other measurement variables. The detection can be effectedspontaneously or else continuously. Furthermore, it is also possible todetect factors which can bring about well-being, stress or externalinfluences on the body of the user, but also events such as eating,periods of sleep, sport or the like. In this regard, reference may bemade for example to the prior art described above.

As an alternative or in addition to the detection of at least onemeasurement variable, the at least one medical function of the networkcan also comprise an actuator function for exerting at least one effecton a body of the user. This can be, in principle, any desired effect, inparticular exerting a stimulus on the body which is suitable, inprinciple, for altering at least one body state and/or for effecting atherapy function. In particular, this can be a chemical and/orpharmaceutical stimulus and/or a physical stimulus, for exampleadministration of a medicament, exertion of an electrical stimulus,exertion of pressure, exertion of temperature (heat or cold) on the bodyof the user or the like. In particular, the at least one actuatorfunction can be a medication function and/or the actuator function cancomprise such a medication function. Thus, e.g., the actuator functionmay comprise the function of an insulin medication, such as the functionof an insulin pump. Alternatively or additionally, however, otheractuator functions can be present.

The medical network is thus set up, in particular after the methoddescribed has been carried out, for carrying out at least one medicalfunction. Furthermore, at least one, and possibly two, three or more ofthe network nodes can be set up for in turn carrying out a nodefunction. In this case, a node function is a function which anindividual network node or an assemblage comprising a subset of thenetwork nodes can carry out independently, if appropriate with provisionof an external energy source and/or after external instigation to carryout this function, for example an external trigger. With regard to saidnode function, reference may be made, in principle, to the descriptionof the network function since, by way of example, the individual networknodes can also carry out the above-described functions, individually orin combination as node functions. By way of example, the at least onenode function can comprise at least one of the following node functions:a sensor function (for example a diagnosis function, wherein referencemay be made by way of example to the above-described sensor functions ofthe network, in particular to the diagnosis functions), an actuatorfunction, in particular a medication function or the like. Otherfunctions from among those described above can also be carried out as analternative or in addition. Furthermore, the at least one node functioncan comprise at least one communication function for exchanging items ofinformation with at least one element not assigned to the network. Saiditems of information can comprise, for example, data, control commandsor the like; in particular, the at least one node function can in thiscase comprise an interface function, for example a wire-basedcommunication function, wireless communication function or communicationfunction that operates via a body of the user. In particular, aBluetooth and/or infrared interface can be included.

As an alternative or in addition, the at least one node function cancomprise at least one communication function for exchanging items ofinformation with at least one user. This exchange can be effected in aunidirectional or bidirectional fashion. By way of example, the at leastone item of information, which can in turn also comprise controlcommands, for example, can comprise visual, acoustic, optical or hapticdata outputs, for example by means of a display. As an alternative or inaddition, data inputting or inputting of control commands can also beincluded, for example by means of one or a plurality of operatingelements or the like.

Once again as an alternative or in addition, a data processing functioncan be included. This can be effected for example by implementing one ora plurality of microprocessors. Once again as an alternative or inaddition, a data storage function can also be included, for example bymeans of at least one volatile and/or non-volatile data memory.Furthermore, likewise once again as an alternative or in addition, atleast one energy obtaining function for generating energy from anenvironment of the network node, for example from a body of the user,can be included. In this respect, so-called energy harvesting, forexample, can be provided in order, for example, to obtain energy for thewhole network or parts thereof, such as for the specific network node,from the environment and/or a body of the user by way of vibrations,heat, pressure or similar stimuli.

Once again as an alternative or in addition, the at least one nodefunction can be at least one clock function for providing a real time.In particular, a UTC (Universal Time Coordinated) can be provided, thatis to say a presently applicable world time. The latter is generallygenerated from a time derived by an atomic clock and generates anidentical counter reading throughout the world. Said reading isgenerally independent of time zones or date lines. By means of thiscounter, it is possible, for example, for events to be temporallyexactly synchronized identically throughout the world, including inmedical technology. The local times can be derived therefrom by means ofan algorithm.

As explained above, the medical network can be set up completely orpartly as a so-called body area network (BAN). In this respect,reference may be made, for example, to the prior art described above.Accordingly, by way of example, two or more of the network nodes can beset up for communicating with one another via a body of a user as signaltransmission medium. Accordingly, the network nodes can havecorresponding electrodes, for example, in order to couple electricalsignals and/or electromagnetic signals into a body of the user or onto abody of the user and/or to couple said signals out of said body.

Further preferred configurations of the method relate to theinitialization step. This initialization step can itself comprise aplurality of sub-steps. By way of example, the initialization step cancomprise, alongside the above-described exchange of the at least oneitem of initialization information, at least one boot step, that is tosay a step in which elementary functions of the network node itself areinitialized without the network node in this case necessarily beingconnected to other network nodes. Boot steps of this type are known, inprinciple, from the field of the designing of electronic devices.

As explained above, the method for setting up the medical network can beset up, in particular, for incorporating new network nodes into thenetwork. This can be effected in the context of a so-calledplug-and-play concept, for example.

Accordingly, the initialization step can be configured for example insuch a way that, in this step, at least one network node which is to benewly inserted into the network is physically assigned to the network.This physical assignment can in one instance comprise a process in whichthe network node which is to be newly inserted is brought spatiallyclose to an already existing partial network or into an already existingnetwork, for example a process of bringing it close in such a way that anear-body network communication can take place. As an alternative or inaddition, an active incorporation can also be effected, for example bymeans of the network node which is to be newly inserted being activelylogged on to the network and/or at least one network node of the alreadyexisting network. This logging-on can be effected by means of so-calledpairing, for example, that is to say a process in which a communicationbetween the network node which is to be newly inserted and the networkor a part of the network is permitted. The pairing can be effected forexample by the inputting of a code, a specific user action that deviatesfrom normal operation, a specific type of the process involving bringingsaid node spatially close in a certain way which usually would not occurduring normal operation of the network, an exchange of items of pairinginformation, or the like, preferably by a user's action.

The logging-on and/or the pairing can comprise one or more means forproviding an authentication and/or for providing a pre-defined level ofprivacy. Thus, during logging on, e.g. by providing an exchange of oneor more log-on codes (such as uni-directionally or bi-directionallybetween one node to be added to the network and at least one node of thenetwork already existing), it might be ensured that no network node isadded to the network which is not supposed to enter the network, such asa network node from a different user getting close to the actual user ofthe network concerned.

Similarly, the method can provide one or more steps for ensuring privacyof the network and/or the user. Thus, the method and/or the network mayprovide means adapted to prevent other users and/or other devices toretrieve information from the network or from one or more of the networknodes. Again, this feature can be realized by unidirectional orbidirectional exchange of authentication information and/or one or morepasswords.

The method can then be carried out in such a way that the network nodewhich is to be newly inserted exchanges the at least one item ofinitialization information with at least one network node alreadypresent in the network. Accordingly, by way of example, when a newnetwork node is incorporated into an already existing network, theinitialization step can be carried out anew. In addition, it isoptionally possible for the at least one self-organization step to becarried out anew before a transition is then made preferably to the workstep.

As described above, the initialization information can comprise at leastone item of information characterizing the network nodes or at least onenetwork node involved in the initialization of the network. Inparticular, the initialization information can comprise at least one ofthe following items of information: an item of information about a typeof at least one of the network nodes, for example a sort of the networknode, a manufacturer, a date of manufacture, a purpose of use, or thelike; an item of information about a function of one of the networknodes, in particular about a medical function, that is to say an item ofinformation about the purpose for which the network node can be used,for example an item of information about a node function of the networknode; an item of information about a configuration of hardware resourcesof one of the network nodes, in particular about a data storage deviceand/or a data processing device of one of the network nodes; an item ofinformation about a communication protocol of one of the network nodes,for example a communication standard or the like; an information about apre-configuration, in particular an information on a calibration and/ora mathematical set-up. The initialization information can comprise inparticular specifically one or a plurality of the network nodes involvedin the initialization step. By way of example, the initializationinformation can relate specifically to the network node which is to benewly incorporated into the network. However, further configurations arealso possible, in principle, for example configurations in which thenetwork node which is to be newly incorporated acquires items ofinformation about other network nodes.

Further advantageous configurations of invention embodiments relate tothe configuration of the self-organization step. In principle, in theself-organization step, it is possible to have recourse to knownconcepts for the self-organization of networks or complex systems. Insystems theory and also in the context of the present invention,self-organization denotes, in principle, any form of system developmentin which the shaping and/or configuring and/or restricting influencesemerge from the elements of the self-organizing system itself, in thiscase from the network nodes. Accordingly, a self-organizing systemgenerally has the properties of complexity, self-reference, redundancyand autonomy. By way of example, it is possible to have recourse tosoftware programs having non-defined (deterministic) program flows, forexample to program flows having fuzzy rules.

In the context of the present invention, self-organization serves todefine a role distribution of the network nodes of the network. The roledistribution is, in principle, any desired scheme which defines thecooperation of the network nodes in the subsequent work step. In thiscase, the self-organization can be configured to the effect that therole distribution is coordinated optimally or at least well for examplewith the type of the network nodes, with the communication capabilitythereof, with the resources thereof and with the node functions thereof.By way of example, the role distribution can comprise at least one ofthe following definitions: determination of at least one network node asmaster node, that is to say as node which at least temporarily controlsat least one other node (slave node); determination of at least onenetwork node as slave node, that is to say a controlled node;utilization of at least one resource of a first network node by at leastone second network node; an interaction of at least two network nodesfor carrying out at least one function which cannot be achievedindividually by the network nodes; a dynamically adaptable set of roledistributions. Other role distributions are also possible, in principle.The latter of the listed possibilities demonstrates that the roledistributions of some or more of the network nodes may change during oneor more of the steps of the method, such as during the work step. Atleast one item of information about the role distribution can be storedin at least one data storage device of at least one of the networknodes. By way of example, this can involve an item of information aboutexisting resources, an item of information about existing functions ornode functions, an item of information about a communication protocol orabout available communications or the like. It is particularly preferredif the at least one item of information about the role distribution isstored in a plurality of data storage devices on a plurality of networknodes, that is to say that redundant data storage is effected. Redundantdata storage can be utilized for example for the purpose that, when oneof the network nodes is removed from the network, the information aboutthe previous role distribution is still available with high probability.

In a further embodiment of the invention, the self-organization step maybe performed in a controlled way, i.e. in such a way that one or more ofthe results of the self-organization step are at least partiallycross-checked with and/or controlled by: one or more boundary conditionsand/or a superordinate authority. Thus, e.g. by pre-determining a fixedset of rules which may not be exceeded or violated, may be provided. Therules generated during the self-organization step may be cross-checkedagainst this fixed set of rules. The superordinate authority may be anexternal computer or computer network or even an external expert, suchas a doctor or nurse, which might be consulted automatically by thenetwork, in order to cross-check the rules generated during theself-organization step.

The method can furthermore comprise at least one log-off step. In thelog-off step, which can, for example, also interrupt one of the stepsmentioned above, at least one network node is removed from the network.This removal may take place in several ways, such as by a controlledremoval of the at least one network node by a user or by afailure-induced removal of the network node. The first case may e.g. beannounced or transmitted to the network or part of the network by theuser himself, such as by initiating a controlled “un-pairing” action.This un-pairing may include one or more steps similar to the pairingaction as described above, such as a user action which usually would notoccur during normal operation of the network, an exchange of un-pairinginformation or the like. This un-pairing step may induce or announce acontrolled removal of the network node by the user. Further,alternatively or additionally, the network or parts thereof (such as atleast one network node remaining in the network) may be adapted todetect the removal of one or more network nodes by itself, especiallyautomatically. Thus, the removal of one or more network nodes may bedetected in the log-off step by at least one network node remaining inthe network, for example by means of a corresponding log-offidentification step. After the log-off step, the self-organization stepis then carried out anew in order to newly define a role distribution ofthe remaining network or of the remaining network nodes. In addition, itis optionally also possible for the at least one initialization step tobe carried out anew, although this is not generally necessary since theinitialization information of the remaining network nodes is generallypresent. The new role distribution of the remaining network can relate,for example, to altered resources, altered network or node functions,altered master-slave role distribution, altered communication structuresor the like.

Optionally, the method can in this case be carried out in such a waythat a warning is issued to a user if, in the renewed self-organizationstep, it is identified that a sufficient functionality of the remainingnetwork no longer exists. This warning can be issued for exampledirectly to a user, for example by means of a corresponding userinterface (e.g. a display, see the description above), and/or indirectlyby means of at least one external element, for example a computerelement connected to the network.

The method can be carried out in particular in such a way that theremoval of the at least one network node from the network is identifiedby interrogation of the presence of the network node by at least onefurther network node and/or by the absence of an expected signal of thenetwork node. By way of example, the at least one further network nodecan send interrogation signals to the network node at regular orirregular intervals, wherein said interrogation signals can be sent toone or a plurality of the network nodes. Said interrogation signals canbring about in regular operation, for example, a response of therespective network node signalling the presence of the network node. Byway of example, a star-type structure, a tree-type structure or astructure organized in some other way can be realized, in the case ofwhich respectively one or a plurality of network nodes send suchinterrogations to one or a plurality of other network nodes. If aresponse signal of the interrogated network node fails to appear, thenfor example removal of the network node from the network can be deducedfrom this. In this case, removal should be understood to mean physicalremoval from the network and/or moreover a failure of the respectivenetwork node, for example by virtue of the occurrence of a malfunctionof the network node or a collapse of an energy supply of the networknode. As an alternative or in addition to interrogation of the presenceof the network node, the removal of this network node can also beidentified by absence of an expected signal of the network node. Thus,by way of example, it is possible to provide a communication scheme inwhich each network node or at least one of the network nodescommunicates signals to at least one further network node at regular orirregular intervals. If these expected signals fail to appear, then theremoval of the network node whose signal has failed to appear from thenetwork can be deduced from this. Various other schemes for identifyingthe removal of the network node from the network are conceivable.

The work step of the method according to the present may further beexecuted at least partly in a self-learned and/or self-trained way.Thus, in this embodiment, one or more of the network nodes or even thewhole network may perform one or more functions during the work step ina way that is not or at least not fully pre-determined before theoperation of the network, but instead may be determined by aself-learning process and/or self-training process. This self-learningprocess and/or self-training process may be performed in such a way thatthe way of operation of the network or of one or more of the networknodes is adapted to the boundary conditions, such as by an optimizationprocedure. Thus, the self-learning may evaluate, e.g. by trial and erroror by evaluating first results of the network operation, the boundaryconditions or the functioning of the network and may improve or evenoptimize the setup of the network, e.g. by using an iterative process.

One particular feature of the production of medical networks comprisinga plurality of network nodes consists in the fact that the medicalnetwork can be set up for performing at least one medical function whichgoes beyond the sum of the individual functions of the network nodes. Inother words, the network nodes may cooperate in such a way that thenetwork may perform at least one function or task which would not bepossible by the network nodes alone, but which is enabled by asynergetic cooperation of the network nodes. In this way, by way ofexample, synergistic effects of the network nodes can be utilized, forexample by signals of different network nodes being combined in order togenerate new items of information, by actuators and sensors beinginterconnected to form control loops, or in some other way. Accordingly,it is particularly preferred if at least two of the network nodes are ineach case set up for performing at least one node function, for exampleone or a plurality of the node functions described above. In this case,a network node can also be set up for performing a plurality of suchnode functions. The self-organization step and the work step can then becarried out in particular in such a way that the function of thenetwork, in particular the medical function, comprises at least onefurther function which goes beyond the sum of the node functions. Saidat least one further function can comprise, for example, at least one ofthe following functions:

-   -   provision of an item of information, wherein the information is        generated by combination of at least two measurement variables        of at least two network nodes;    -   driving or controlling of at least one first network node by at        least one second network node, such as by setting up a        master-slave-system;    -   a control function, wherein at least one first network node with        an actuator function is subjected to open-loop and/or        closed-loop control by the comparison of at least one        measurement value of at least one second network node with at        least one measurement function with at least one desired value.

A combination of the above-mentioned, further functions and/or otherfunctions is also conceivable. In principle, it is also possible toimagine other synergistic effects between the node functions and torealize them in the context of the present invention.

In a further aspect of the present invention, the method comprises atleast one monitoring step. This monitoring step can be carried out forexample in parallel with the other method steps, in temporallyoverlapping fashion, intermittently (for example at regular or irregularintervals) or at the same time. The monitoring step can be configuredfor example as the topmost entity of the network and/or can be realizedfor example in the background on one, a plurality or all of the networknodes and/or on a master node. The monitoring step is set up formonitoring at least one result of the self-organization step and/or ofthe work step and for carrying out at least one fault routine uponidentification of a deviation from a standard or of an anomaly. Atypical deviation can consist, for example, in a role distributiondeviating from a multiplicity of possible predetermined roledistributions in such a way that a fault must be present in theself-organization step. Furthermore, by way of example, a plausibilityconsideration can be carried out in order for example to compare resultsof the work step and/or of the self-organization step with specificlimit values or limit functions and/or a plurality of predeterminedresults. In this way, by way of example, oscillations of the system suchas can occur in self-organizing systems can be identified. Acorresponding standard with which comparison can be made can be storedfor example in the form of one or a plurality of standard values and/orstandard functions and/or possible standard states in at least one datastorage device of at least one network node. The monitoring step can becarried out on one or a plurality of network nodes, for example, asexplained above, a master node and/or a network node specificallyconfigured for this task.

The background of this configuration is that medical systems, forexample diagnostic and/or actuator-appertaining networks, nowadaysgenerally consist of complex individual modules with different handlingin start-up, calibration and the like. This means, however, that theself-organization and the subsequent standard operation of the medicalnetwork generally have to be subjected to a specific control, which canfunction as a last entity, for example, and which can intervene in themedical network in a regulating fashion before unexpected states and/orfunctions which cannot be predicted from the individual network nodesoccur. In this way, it is possible to identify and, if appropriate,prevent for example non-plausible role distributions as a result of theself-organization step and/or non-plausible functions of the network orof individual or a plurality of network nodes.

Upon identification of a standard deviation, the monitoring step carriesout at least one fault routine. In this case, a fault routine should beunderstood to mean a regulating intervention in the function of themedical network and/or the function of at least one of the network nodesand/or a regulating intervention in the role distribution. The faultroutine can comprise for example one or a plurality of the followingmeasures: an intervention in the role distribution (for example areorganization of a master-slave assignment, a reorganization of theresource utilization or the like); an activation and/or deactivation ofone or a plurality of network nodes; an issuing of a warning to a userand/or an element not assigned to the network (for example an externalcomputer connected in a communication link to the network, for example);an intervention in at least one function of the network; a deactivationof the network or at least one network node. Combinations of theabovementioned measures and/or of other measures are also possible, asis a different configuration of the fault routine.

In addition to the method in one or more of the configurations describedabove, a medical network for carrying out at least one medical functionis furthermore proposed. The medical network comprises at least twonetwork nodes, and can include three, four or more network nodes,wherein at least two of the network nodes are set up for carrying out amethod according to any of the preceding claims. Accordingly, withrespect to the medical network, reference may be made to the abovedescription of the method.

The proposed method and also the proposed medical network have numerousadvantages over known methods and networks. Thus, it is possible torealize even complex medical networks in which two, three or morenetwork nodes interact with their node functions, such that synergisticeffects that go beyond the individual functions of the network nodes canbe utilized. As an alternative or in addition to deterministic rules forcontrolling the network, the self-organization of the network can followfuzzy rules, for example, in particular rules which lead to resultswhich are not predictable on the basis of the properties of theindividual network nodes.

The medical network can be configured for also detecting extracorporealevents, such as eating, sleeping, sport and stress, for example, andconcomitantly incorporating them into the functionality.

The network can be set up, in particular, for ascertaining and/ormaintaining and/or influencing body states. Self-organizing,self-learning and self-synchronizing structures can be realized in thiscase. In the case of the network, the plug-and-play concept, inparticular, can be supported in such a way that a user, for example apatient or a care giver, only has to perform a small number of measuresduring the initial application, during expansion or duringreconfiguration or reconditioning, such as, for example, calibrations ormanual supports.

The medical network, for example by virtue of the provision of acommunication network node having at least one communication functionfor communication with an element outside the network, can also,automatically link into superordinate systems or superordinate networks,authenticate itself and, if appropriate, log off again. This can be donefor example at the level of the link layer and the protocol layeraccording to the OSI 7-layer standard. A possible rejection of thenetwork can also be realized.

The self-learning system network nodes can have, upon start-up, adeterministic start rule set in order to perform basic functions. Thiscan be effected for example in the context of the initialization step,for example in the context of a boot step of the initialization step.The start rule functions and/or basic functions can be utilized, forexample, in order to produce a defined start state of the entirenetwork, of a part of the network or of individual network nodes of thenetwork. Furthermore, in this way, establishment of communication can beinitialized, hardware drivers can be loaded, or the like.

From the data collected since the start-up of the network, the networkor individual or a plurality of the network nodes, for exampleself-learning isolated modules, can for example also collectexperiences, assess the data and, in a manner resulting therefrom, ifappropriate, independently alter rules and adapt and even alter initialmodes of behaviour or the role distribution. By way of example, theself-organization step can be carried out repeatedly, for example by theprocessing of results of the work step, which can likewise be carriedout repeatedly, in order to adapt and, if appropriate, to optimize therole distribution.

If further network nodes are added, for example self-learning and/ordetermined modules, then the behaviour of individual modules, of aplurality of modules or of the entire network can change further fromthe knowledge of all or new system properties and this can in turn havereactions on individual modules and/or the entire network. Such a systemcorresponds to a feedback and/or positive feedback system and generallyrequires rules and criteria, for example stability criteria similar tothose of closed-loop control technology, for damping in order to avoidoscillations, for example. Such functions can be implemented inparticular in the context of the monitoring step described above.

Network nodes which enter into operation near-instantaneously ortemporally at long intervals establish a link with one another and thengenerally undergo self-organization. This can comprise for example thedefinition of master and slave roles and/or priority levels, which canbe defined in the context of the role distribution. Priority levels canfor example initially be defined beforehand, for example on the basis ofthe predefined tasks, but can also change in the course of time, forexample as a result of experiences or on account of the present dataposition. Master and slave roles can also change dynamically, forexample on account of a suddenly increased amount of data, on account ofwhich the master can temporarily hand over the organization tasks to adifferent module. The tasks can, in principle, be divided among thenetwork nodes temporarily or permanently.

Network nodes having actuator functions can also be included in thelearning process. Thus, by way of example, the stimuli of the actuatorscan be altered, if appropriate, on account of the items of informationfrom the networked sensor modules. Furthermore, experience- andknowledge-based linkages and derivations of rules and conclusions can becarried out, for example in the context of so-called expert systems.Expert systems have already become established, in principle, in thefield of medical technology.

In principle, the network, all the network nodes or else one or aplurality of the network nodes can be subjected to a superordinate, alsoextracorporeal calibration concept. Accordingly, the network orindividual or a plurality of network nodes can also be set up in such away that calibration values are communicated to the network fromoutside, for example in the context of a hierarchy, wherein thecalibration values have a high prioritization. For this purpose, thenetwork can have a communicator module as network node, for example, bymeans of which module calibration values of this type can be input. Thenetwork can be prioritized for example in such a way that suchcalibration values impressed from outside have to be accepted. Moreover,by way of example, rules for the organization of interventions byauthorized outsiders, for example a physician and/or a helper, can becreated, and can be communicated to the network nodes or to individualnetwork nodes. This can be done for example in the context of aproduction step and/or in the at least one initialization step. Saidrules can be configured for example in such a way that, in the case ofoccurrence of an intervention by an outsider having correspondingauthorization, said rules permit such an intervention.

In the context of the monitoring step described above, it is possible tocreate and implement suitable validation methods for changing programsand self-organizing systems in the medical network. Thus, by way ofexample, it is possible to test the change threshold to which there isreaction and whether these reactions of the network and/or of individualor a plurality of network nodes are then actually plausible, for exampleby checking their conformity with generally valid rules. If the modes ofbehaviour of the network or of individual components or system partsdeviate from long-term empirical values or behaviour, then it ispossible to discriminate faults from the network nodes, for example onthe basis of mathematical algorithms, and spontaneously to derivefail-safe measures or to generate fault messages. This can be done forexample in the context of the fault routine described above. In theworst case, this can culminate in a shutdown of individual network nodesor of the entire network, or in messages on external display devices.Defective states should possibly also be communicated to the user or theenvironment by means of suitable stimuli. By way of example, stimulatorssuch as a vibrator, electrical stimulation, light signals or the likecan be provided for this purpose. The degree of discrimination can inturn be adapted depending on what is learned, and can be adjustable byexternal authorities, for example experts.

Modules of complex systems do not necessarily have a real-time clock. Inthe context of the proposed network, however, one, a plurality or all ofthe network nodes can be configured with such a real-time clock (RTC).The availability of real time may be necessary and may be used withinthe present invention for synchronizing two, more than two or even allof the activities and/or functions within the network. Particularly inthe context of realizing near-body networks, in particular BANs (BodyArea Network), however, at least one real-time system of this typeshould be integrated in the context of the present invention.Accordingly, it is particularly preferred if at least one of the networknodes, as explained above, comprises such a real-time clock. This can beeither a defined module or a defined network node, or an allocation canbe effected in the context of the self-organization step, for example.Such a network node having a real-time clock should have specifichardware for this purpose. Said hardware either provides anuninterrupted energy supply for operating the real-time clock directlyafter the production date, or obtains the real time after start-up froman external reference time system (for example via a PC, a network, theInternet, GPS, a radio controlled clock or the like), for example bydirect contact to the outside or via a network node with a communicatormodule.

In the context of the proposed network, synchronization with a secondaryevent can also be effected. In this way, by way of example, sportingactivities, mastication, swallowing or the like can be detected, forexample by means of specific network nodes having sensor modules set upfor this purpose. By way of example, provision can be made of one or aplurality of network nodes having acoustic sensors which identify thetype of food on the basis of mastication noises and/or detect the amountof food on the basis of swallowing peristalsis. By way of example, inthis respect, reference may be made to O. Amft: Automatic dietarymonitoring using on-body sensors: detection of eating and drinkingbehaviour in healthy individuals, dissertation ETH Zürich, 2008. Networknodes of this type can also optionally be introduced into the networkand act for example in accordance with the primary modules. If modulesare not available, such items of secondary information can, however, canstill be inputted manually by means of an external communicator, forexample.

The network comprises, as explained above, preferably at least onenetwork node which is set up for performing a communication function forexchanging items of information with at least one user. Such a networknode can also be referred to as a communicator module or be configuredas a communicator module. This network node can maintain contact withthe environment, for example. This can be effected for example by meansof free field radio, that is to say by means of a radio system in whichthe electromagnetic wave is completely released from the antenna. Suchan interface can correspond to suitable and known radio standards, forexample Bluetooth, W-LAN, IEEE 802, but can also have a proprietarynature. Near field communication (NCF) can also be used, that is to saycommunication in which only the magnetic field component is utilized. Asan alternative or in addition, optical transmission links are alsoconceivable, but they are preferably not used in the case ofsubcutaneous nodes of the network since such optical transmission linksgenerally necessitate a visual link.

Within the network, specific protocols can exist, for example, which canpreferably likewise be modified as required. Communication protocolsbetween the communicator module and the environment can be configured inaccordance with customary standards, for example.

Furthermore, the network can also be set up for carrying out logging.For this purpose, by way of example, one or a plurality of the networknodes can have a logging function, such as a data logging function, forexample in the context of so-called data logging. By way of example,program and rule modifications of the self-learning network can beconcomitantly logged for control and verification purposes, in whichcase corresponding compilation possibilities can also be provided. Thedata logging function specifically may be provided for compliancepurposes.

Furthermore, in the case of the individual network nodes or modules,there can be a possibility of learning modes of behaviour of third-partyproducts, even if these are defined deterministically, if appropriate,and of concomitantly incorporating them into their own rules, or ofintegrating such modules in the network. This results in a high degreeof interoperability. In this way, it is also possible, for example, forsuch learning procedures to be carried out interactively, for example ina manner controlled by a user.

Summarizing the findings above:

Item 1: A method for setting up a medical network for carrying out atleast one medical function, wherein the medical network comprises atleast two network nodes wherein the network nodes are set up forcommunicating with one another, wherein the method comprises at leastthe following steps:

at least one initialization step, wherein at least two network nodesexchange at least one item of initialization information in theinitialization step, wherein the initialization information comprises atleast one item of information characterizing the network nodes;

at least one self-organization step, wherein the network nodes define arole distribution of the network nodes;

at least one work step, wherein the network carries out the at least onemedical function in the work step, wherein at least two of the networknodes interact in accordance with the role distribution defined in theself-organization step.

Item 2: The method according to the preceding item, wherein the roledistribution is defined by making use of the at least one itemcharacterizing the network nodes.

Item 3: The method according to any of the preceding items, wherein themethod comprises a comparison of the at least one item of informationcharacterizing the network nodes, wherein the definition of the roledistribution of the network nodes at least partly is based on a resultof this comparison.

Item 4: The method according to any of the preceding items, wherein theself-organization step is carried out in such a way that the roledistribution comprises a determination of at least one network node asmaster node and a determination of at least one network node as slavenode.

Item 5: The method according to one of the preceding items, wherein thenetwork node having the most powerful hardware resources is defined asthe master node.

Item 6: The method according to one of the two preceding items, whereinthe network node having the most time-critical function is defined asthe master node.

Item 7: The method according to one of the three preceding items,wherein at least two network nodes are capable of taking over the roleof the master node.

Item 8: The method according to any of the preceding items, wherein therole distribution relates to at least one of: a division of resources; areciprocal control; a communication among one the network nodes; acommunication with at least one element outside the medical network.

Item 9: The method according to any of the preceding items, wherein inthe self-organization step at least two of the network nodes, preferablyat least three of the network nodes and most preferably all of thenetwork nodes of the medical network, define the role distribution ofthe medical network.

Item 10: The method according to any of the preceding items, wherein themethod is adapted to change the role distribution of the network nodesduring operation of the medical network.

Item 11: The method according to any of the preceding items, wherein themedical function of the network comprises at least one of the followingfunctions: a sensor function for detecting at least one measurementvariable of a body of a user, in particular a diagnostic function; anactuator function for exerting at least one effect on a body of a user,in particular a medication function.

Item 12: The method according to any of the preceding items, wherein atleast one of the network nodes is set up for carrying out at least oneof the following node functions: a sensor function; an actuatorfunction; a communication function for exchanging items of informationwith at least one element not assigned to the network; a communicationfunction for exchanging items of information with at least one user; adata processing function; a data storage function; an energy obtainingfunction for generating energy from an environment of the network node;a clock function for providing a real time.

Item 13: The method according to any of the preceding items, wherein atleast two of the network nodes are set up for communicating with oneanother via a body of a user as signal transmission medium.

Item 14: The method according to any of the preceding items, wherein, inthe initialization step, at least one network node which is to be newlyinserted into the network is physically assigned to the network, whereinthe network node which is to be newly inserted exchanges theinitialization information with at least one network node alreadypresent in the network.

Item 15: The method according to any of the preceding items, wherein theinitialization information comprises at least one of the following itemsof information: an item of information about a type of one of thenetwork nodes; an item of information about a function of one of thenetwork nodes, in particular about a medical function; an item ofinformation about a configuration of hardware resources of one of thenetwork nodes, in particular about a data storage device and/or a dataprocessing device of a network node; an item of information about acommunication protocol of one of the network nodes; an information abouta pre-configuration, in particular an information on a calibrationand/or a mathematical set-up.

Item 16: The method according to any of the preceding items, wherein theself-organization step is carried out in such a way that the roledistribution comprises an interaction of at least two network nodes forcarrying out at least one function which cannot be achieved individuallyby the network nodes.

Item 17: The method according to any of the preceding items, wherein theself-organization step is carried out in such a way that the roledistribution comprises a dynamically adaptable set of roledistributions.

Item 18: The method according to any of the preceding items, wherein theself-organization step is carried out in such a way that the roledistribution comprises a utilization of at least one resource of a firstnetwork node by at least one second network node.

Item 19: The method according to any of the preceding items, wherein, inthe self-organization step, at least one item of information about therole distribution is stored in at least one data storage device of atleast one of the network nodes, preferably in data storage devices of aplurality of network nodes.

Item 20: The method according to any of the preceding items, wherein theself-organization step is controlled by one of the following: apre-definition of boundary conditions; a confirmation of at least oneresult of the self-organization step by at least one superordinateauthority.

Item 21: The method according to any of the preceding items, furthermorecomprising at least one log-off step, wherein at least one network nodeis removed from the network in the log-off step, wherein, after thelog-off step, the self-organization step is carried out again in orderto newly define a role distribution of the remaining network.

Item 22: The method according to the preceding item, wherein a warningis issued to a user if, in the renewed self-organization step, it isidentified that a sufficient functionality of the remaining network nolonger exists.

Item 23: The method according to any of the preceding items, wherein atleast two of the network nodes are in each case set up for performing atleast one node function, wherein the self-organization step and the workstep are carried out in such a way that the function of the networkcomprises at least one further function going beyond the sum of the nodefunctions.

Item 24: The method according to the preceding item, wherein the atleast one further function comprises at least one of the followingfunctions: provision of an item of information, wherein the informationis generated by combination of at least two measurement variables of atleast two network nodes; driving of at least one first network node byat least one second network node; a control function, wherein at leastone first network node with an actuator function is subjected toopen-loop and/or closed-loop control by the comparison of at least onemeasurement value of at least one second network node with a measurementfunction with at least one desired value.

Item 25: The method according to any of the preceding items, furthercomprising at least one monitoring step, wherein the monitoring step isset up for monitoring at least one result of the self-organization stepand/or of the work step and for carrying out at least one fault routineupon identification of a standard deviation.

Item 26: The medical network for carrying out at least one medicalfunction, wherein the medical network comprises at least two networknodes, wherein at least two of the network nodes are set up for carryingout a method according to any of the preceding items.

BRIEF DESCRIPTION OF THE DRAWINGS

Further details and features of embodiment of the invention will becomeapparent from the following description of exemplary embodiments, inparticular in conjunction with the dependent claims. In this case, therespective features can be realized by themselves or as a plurality incombination with one another. The invention is not restricted to theexemplary embodiments. The exemplary embodiments are illustratedschematically in the figures. In this case, identical reference numeralsin the individual figures designate elements which are identical orfunctionally identical or correspond with regard to their functions.

FIG. 1 shows an exemplary embodiment of a network according toembodiment of the invention.

FIG. 2 shows a typical program structure of one, a plurality or all ofthe network nodes of the network.

FIG. 3 shows an example of a method for setting up a medical networkaccording to the embodiments of the invention.

FIG. 4 shows a detail illustration of an assessment step and rulecreation step of the method in accordance with FIG. 3.

FIG. 5 shows exemplary embodiments for the energy supply of the networkin accordance with FIG. 1.

DETAILED DESCRIPTION

An exemplary embodiment of a network for carrying out at least onemedical function is illustrated in highly schematic fashion in FIG. 1.The network 110 comprises a plurality of network nodes 112, which areconnected in a communication link with one another directly orindirectly and uni-directionally (single-headed arrow) or elsebi-directionally (double-headed arrow), in such a way that each of thenetwork nodes 112 can communicate with at least one further network node112. This communication is effected in part by means of a body areanetwork 114, which is designated by BAN in FIG. 1, in other words anetwork in which the network nodes 112 communicate with one anotherwhilst at least partly incorporating a body of the user, for example bymeans of electrical signals being exchanged via the body of the user.For this purpose, the network nodes 112 can have correspondingelectrodes, for example, which can directly or indirectly couple suchelectrical signals into the body or couple them out of the body.Furthermore, the network 110 can comprise, however, as an alternative orin addition to the network nodes 112 of the body area network 114,network nodes 112 which are not associated with the body area network114 and which can communicate with other network nodes 112 by means of adifferent communication technology, for example by means of free fieldradio 116, radio-frequency signals (e.g. RFID, Radio FrequencyIdentification), Near Field Communication (NFC), real-time communication(UTC), GPS or radio controlled clock.

The network nodes 112 in the network 110 in accordance with FIG. 1 canbe configured wholly or in part as modules, that is to say as elementswhich, in principle, can be handled independently of one another, whichare not necessarily physically connected to one another by a housing andwhich, in principle, can perform at least one network functionindependently of one another. Thus, by way of example, at least one ofthe network nodes 112 can perform at least one function of an actuator118, at least one of the network nodes 112 can perform at least onefunction of a sensor 120, at least one of the network nodes 112 canperform a function of a data storage device 122, which can be performedat least temporarily, at least one of the network nodes 112 can performa function of a stimulator 124, for example for issuing an alarm, forexample in the form of a vibrator. Furthermore, at least one of thenetwork nodes 112 can assume for example a function of an externalcommunicator 126, for example in order to be connected to at least oneelement outside the network 110 by means of free field radio or othersof the technologies described above or via a different type ofinterface. Furthermore, one of the network nodes 112 can be configuredas a wristwatch 128, for example, which can comprise one or a pluralityof operating elements, for example, and one of the network nodes 112 canbe configured for example with a display 130 and/or an interface 132.

The individual network nodes 112 can for example each compriseconstituent parts which can support the performance of the respectivenode function. Thus, the individual modules of the network node 112 canfor example each comprise a part which is specifically adapted for thefunction of the network node 112. By way of example, one or a pluralityof the network nodes 112 can comprise a specific sensor part and/oractuator part. Furthermore, a controller can be provided for thisfunctionality, for example an electronic controller and/or an arithmeticlogic unit or a data processing device, for example in the form of amicrocontroller. These can have clocking, for example. In principle,depending on the complexity of the task, it is also possible to use forexample parallel arithmetic logic units in one or a plurality of thenetwork nodes 112, or digital signal processors (DSP). Furthermore, one,a plurality or all of the modules of the network nodes 112 can compriseprogram and/or data storage devices, and also unidirectional and/orbidirectional communication devices and/or interfaces for communicationwith other network nodes 112. Furthermore, in all, a plurality of orindividual network nodes 112, provision can be made of devices forobtaining energy and/or for providing energy, and/or devices for energymanagement, for example in the form of primary batteries, secondarybatteries, inductive energy coupling-in, energy harvesting or the like,which will be explained in greater detail below with reference to FIG.5. As an alternative or in addition, the network nodes 112 can also beset up completely or in part for the adaptation of the supply dependingon the field of use.

The optional stimulator 124 can be set up for example for outputtingphysiological stimuli, for example in the form of a warning. At leastone of the network nodes 112 can optionally also comprise, apart from atleast one sensor 120, simultaneously also at least one actuator 118, forexample an actuator for administering a substance. It is thus possibleto realize integrated modules, for example so-called “Closed Loops”. Theterm integrated module generally denotes a module in which an actuator118 and a sensor 120 can be spatially situated relatively closetogether. However, a glucose sensor generally has to be at a minimumdistance from an insulin feed, for example, since otherwise the glucoseto be measured is directly influenced by the insulin that is fed (shortcircuit).

During the performance of the method, a program is executed on all or atleast some of the network nodes 112, which program can be realized as asoftware program for example. In this case, the individual programs ofthe individual network nodes 112 considered separately can be regardedas programs, or the overall functionality of the network 110 can bedescribed by an overall program which is decomposed into numerousindividual program modules of the network nodes 112. One example of aprogram of this type is illustrated in FIG. 2. This program can becomposed for example of a boot sector 210 in each case. Said boot sector210 comprises, for example, a loading program for each or at least someof the network nodes 112. This part of the program can establish forexample the basic operational readiness of the network nodes 112, forexample of a microcontroller of the network nodes 112, after the start.

Furthermore, the program in accordance with FIG. 2 comprises a set offixed rules 212. These fixed rules 212 may or even should comprise forexample rules for an initialization step of the proposed program such aswas explained above and will also be presented below by way of examplewith reference to FIG. 3. These fixed rules 212 can compriseunchangeable fundamental rules, for example. This set of fixed rules 212can contain, by way of example, driver programs for hardware, hierarchydeclarations, interrupt handling, interoperability rules or the like.Besides the initialization step, these fixed rules 212 can also compriserules for the work step, that is to say rules which comprise the actualnode function of each or of a plurality of the network nodes 112.

Furthermore, the program in accordance with FIG. 2 comprises an adaptiveprogram part 214. By way of example, variable, self-learning assemblystructures can be combined in this adaptive program part 214. By way ofexample, this adaptive program part 214 can relate to the definition ofparameters, to logical conditions, to algorithms, to module managementwith regard to a role distribution, to communication rules, to protocolsor the like. Accordingly, this adaptive program part 214 shouldessentially be ascribed to the self-organization step described above.

In accordance with these assignments, in FIG. 2 by way of example theinitialization step is designated by the reference numeral 216, theself-organization step is designated by the reference numeral 218 andthe work step is designated by the reference numeral 220.

The program parts of the program in accordance with FIG. 2 can in turnbe uni-directionally or bi-directionally linked to one or a plurality ofoptional databases 222 and/or data storage devices. These can beconfigured completely or in part in centralized or else decentralizedfashion, redundant data storage preferably also being used.

In the case of the program in accordance with FIG. 2 and in the network110 in accordance with FIG. 1, software and/or hardware structures canadapt to new tasks. Thus, by way of example, one or a plurality of thenetwork nodes 112 can undertake the role of a master 134 temporarily orfor a longer time, whereas one or a plurality of the network nodes 112can undertake the role of a slave 136 temporarily or permanently. Thiscan be effected by adaptation of the software structures. As analternative or in addition, hardware structures can also generally beadapted. Thus, by way of example, logic arrays can temporarilyinterconnect logic functions. By way of example, so-calledField-Programmable Gate Arrays (FPGAs) can be used for this purpose.Analogue functions can also be temporarily adapted to the tasks, suchas, for example, filter time constants, gain factors or the like.

In order to be able to carry out comprehensive data logging (for examplefor the handling of subsequent compliance cases) in conjunction withreadily manageable storage outlay, the data are preferably highlycompressed, for example by means of a redundancy filter. In this case,by way of example, data sampling rates and dynamic resolution for datareduction can be adapted to the specific limiting frequency or signalmagnitude of the function. In the case of a blood glucose measurement,for example a continuous blood glucose measurement, sampling can beeffected for example with a frequency of 1 Hz at a resolution of 10-12bits.

The programs and data of the network 110 can be protected bycorresponding encryption, for example, against unauthorized access andunauthorized use or undesired or unauthorized alteration from outside.

The network nodes 112 or the modules can, by way of example, beimplanted at the body, on the skin, under the skin or in deeper layersin the body, or be kept there temporarily. By way of example, one or aplurality of the network nodes 112 can be configured as stomach and/orintestinal camera, glucose sensor, temperature sensor or sensor in thebloodstream. In this case, by way of example, network nodes 112 ormodules can be supplied with energy from the environment. This isindicated by way of example in FIG. 5, in which the network 110 inaccordance with FIG. 1 is illustrated again symbolically and without anyclaim of completeness. Thus, by way of example, at least one of thenetwork nodes 112 or a module can comprise an energy store 510. This canbe a primary or secondary battery, for example. As an alternative or inaddition, at least one of the network nodes 112 can be configured with adevice 512 for energy harvesting By way of example, said device 512 candraw energy from the environment in the form of electrochemical energy,in the form of temperature differences, in the form of mechanical energy(for example vibrations) or the like. Such modules for the purpose ofenergy harvesting are known in principle.

Once again as an alternative or in addition, one or a plurality of thenetwork nodes 112 can be equipped with a device 514 for inductive energysupply and/or for capacitive energy supply. By way of example, networknodes 112 arranged just under the surface of a user's skin can besupplied with energy inductively. Such modules or network nodes 112 cancomprise, for example, a housing appropriate for the task, for example astainless steel capsule for implants, a plastic housing with plaster forexternal securing on the skin or the like. The module components arepreferably designed to be biocompatible and for staying in the body fora relatively long period, in particular with regard to a thermal loadingcapacity, an insensitivity to moisture, or the like. The device 514 caninteract with an external energy supply device 516, which can coupleenergy into the device 514 and the associated network node 112inductively, for example.

FIGS. 3 and 4 illustrate by way of example an exemplary embodiment of amethod for setting up a medical network 110 for carrying out at leastone medical function. As explained above, setting up can in this casecomprise primary new creation of a network 110 of this type,modification of a network and, if appropriate, standard operation of anetwork 110 of this type.

The method necessitates, in principle, the physical assignment of atleast two, preferably three or more of the network nodes 112 to thenetwork 110. This can be effected for example by the network nodes 112being attached to a body, implanted in the body or assigned to thenetwork 110 in some other way. If appropriate, this can also be effectedby means of corresponding aids, such as, for example, insertion aids,needles or the like. Directly after the start of establishment ofoperation, which is designated by the reference numeral 310 in FIG. 3,and also, if appropriate, after a boot program has been carried out, themodules or network nodes 112 can commence their primary node function,which is designated by the reference numeral 312 in FIG. 3. This canalready be part of the work step 220. As an alternative, said work step220 can also be commenced at a later point in time. The primary nodefunction can consist, for example, in the original task of the networknodes 112, for example in measurement of glucose after making contactwith a battery, an actuator function or the like. Furthermore, thenetwork nodes 112 can, for example, collect data (reference numeral 314in FIG. 3) and assess said data (reference numeral 316 in FIG. 3). Steps314 and 316 can likewise be part of the work step 220.

Furthermore, in the case of the method in accordance with FIG. 3, atleast one initialization step is carried out. In this initializationstep 216, at least two of the network nodes 112 communicate with oneanother and exchange in a unidirectional or bidirectional fashion atleast one item of initialization information comprising at least oneitem of information characterizing the network nodes, i.e. all, some orat least one of the network nodes. This method step of communicationwith at least one other module is designated by the reference numeral318 in FIG. 3.

By way of example, the network nodes 112 can communicate and seekpartner modules in and/or on the body or in proximity to the body. Ifother network nodes 112 of this type are found, then a self-organizationstep 218 can be carried out, for example, which can comprise a pluralityof sub-steps in the program in accordance with FIG. 3. The aim of thisself-organization step is to define a role distribution of the networknodes 112 of the network 110. This role distribution can concern forexample the interaction of the network nodes 112, for example adistribution of the functions as master 134 and slave 136, for exampleby identification of which network node 112 has the optimum resourcesfor the respective role, for example an optimum microcontroller, inparticular a microcontroller having high computing power and/or a highclock frequency for the function of the master 134. As an alternative orin addition, the role distribution can also comprise the functionalityof the entire network 110 and define for example at least one functionof the network 110 which is possible only as a result of the interactionof a plurality of network nodes 112 and which goes beyond the sum of theindividual functions of the network nodes 112.

Thus, the self-organization step 218 can comprise for example acoordination process which comprises a pairing and defines master-slaveroles, for example. The linking to the body area network 114 makes itpossible to ensure, for example, that only the modules or network nodes112 attached in and/or on or in proximity to the body begin acommunication and an unambiguous pairing is thereby effected. In orderto prevent, if appropriate, modules from another person from being ableto be linked into a body area network, it is possible, by way ofexample, for signal levels to be discriminated or intensity patterns tobe evaluated. Thus, a body area network in the body will generally havea certain constancy.

Furthermore, in the initialization step 216 or else in theself-organization step 218, a search for an external communicator 126can also be carried out actively by one or a plurality of network nodes112. This can involve, for example, a specific network node 112 or aspecific module which establishes a connection between the body areanetwork 114 and an outside world, for example a bearer or a care giver.If such an external communicator 126 is found, then the network 110attempts to connect itself to the outside world preferably via saidexternal communicator and, for example, via the display 130. As analternative or in addition, a display 130, as shown in FIG. 1, can alsoitself be part of the network 110, for example in the context of awristwatch 128 having a corresponding display. If an externalcommunicator 126 is not found, then the network 110 can preferablynevertheless commence its work, for example the initialization step 216,the self-organization step 218 and/or the work step 220, for example bymeans of synchronization being carried out and/or by means of primaryfunctions of the individual network nodes 112 or synergistic functionsof a plurality of network nodes 112 being carried out.

The external communicator 126 can also be linked into the network 110 bymeans of interactive handling by a user, for example by bringing it inproximity to the body. By way of example, specific mechanicalprecautions, a skin contact, an RFID contact or the like can be carriedout for this purpose.

Parameterization data, calibration data or similar data can be requestedmodule-specifically if an external communicator 126 is available. Themodules or network nodes 112 can then work and stay in a basic function,for example collect and/or log un-calibrated data, until suchparameterization data and/or calibration data are available. Ifcalibration data are not made available within an appropriate period oftime, then it is possible, by way of example, to effect a suitable neworganization with a message, provided that the latter can betransmitted, or, if appropriate, a termination of function.

Furthermore, master and/or slave roles are preferably defined in theself-organization step 218. This method step is designated symbolicallyby the reference numeral 320 in FIG. 3. If new network nodes 112 areadded to the network 110, then these relationships can be distributedanew, for example by means of the initialization step 216 and/or theself-organization step 218 or parts of these steps being carried outanew. By way of example, the master role can be allocated to thatnetwork node 112 or module which has the most time-critical application,for example an EEG module. Efficient interrupt handling can be organizedin this way. As an alternative or in addition, the network node 112 orthe module which has the most time between the individual actions canalso be allocated the role of the master 134, since it then also hastime for further management tasks.

In general, one, a plurality or all of the network nodes 112 can have atleast one item of property information which characterizes therespective network node and can thus be part of the characterizinginformation. In the initialization step 216, this characterizinginformation can be exchanged one-way or reciprocally and be comparedwith one another in order to carry out optimum self-organization in theself-organization step 218. Thus, the property descriptions can becompared and the properties of the network nodes 112 can be mutuallypresented in order that other network nodes 112 can assess them and, ifappropriate, can include them in their task set. By way of example, aninsulin pump can acquire items of information from a glucose sensor andthereby control the release of insulin. Furthermore, by way of example,a temperature module and/or a food ingestion module can be added. Theinsulin module can, after an interactive confirmation, if appropriate,then incorporate the items of information with respect to the algorithmand modify the insulin control.

These method steps of self-organization are designated symbolically bythe reference numerals 322, 324 and 326 in FIG. 3. Thus, by way ofexample, the reference numeral 322 designates outputting of items ofinformation to other network nodes 112 or external experts. Thereference numeral 324 designates by way of example the interrogation ofitems of information from other network nodes or from experts. Thereference numeral 326 generally designates the module or systemmanagement for the management of one, a plurality or all of the networknodes 112. The steps 322 to 326 are symbolically assigned to theself-organization step 218 in FIG. 3. As an alternative or in addition,however, these sub-steps can also be assigned to other steps of theprogram, for example to the work step 220. Thus, the initialization step216, the self-organization step 218 and the work step 220 can alsojointly utilize one or a plurality of sub-steps of the program inaccordance with FIG. 3. Further, the method according to FIG. 3 mayinclude one or more steps of time synchronization 340. In FIG. 3, as anexample, an interaction of the time synchronization 340 with the step ofmodule or system management 326. Alternatively or additionally, othersteps of the method may be time-synchronized.

Furthermore, in FIG. 3, the reference numeral 316, as explained above,designates a sub-step of the assessment of the data. This sub-step 316can likewise be part of the work step 220 or, as an alternative or inaddition, part of the self-organization step 218. The sub-step ofassessment 316 is shown by way of example again in a more detailedillustration in FIG. 4. This sub-step can be carried out for example inone of the network nodes 112 or in a plurality of said network nodes 112and can comprise for example evaluation and assessment of data 328, forexample dedicated data of the respective network node 112 and/ormoreover other network nodes 112. By way of example, the assessment ofthe data can make use of one or a plurality of filter algorithms. Forassessing the data, by way of example, the format of the data can beadapted and/or assessed, time criteria can be employed, the dynamicrange of the data can be influenced or evaluated, or a statisticalanalysis and/or pattern recognition of the data can be carried out.Combinations of the abovementioned evaluations and/or other evaluationsare also conceivable.

Furthermore, items of information from other network nodes 112 aredesignated by the reference numeral 330 in FIG. 4. By way of example, inthis case it is possible to check authenticity, plausibility, frequencyor similar criteria, or it is possible to employ discriminatorthresholds. Combinations of the abovementioned possibilities are alsoconceivable.

Further, as illustrated in FIG. 4, besides the data evaluation 328 andthe information 330 from other network nodes 112, a fixed set of rules331 may be used as a basis for the creation 332 of new rules.

The assessment 316 of the data can take place with time synchronization340, for example. By way of example, time synchronization 340 with UTCcan be effected. This can be effected in particular in the case ofbattery-backed network nodes 112 or network nodes 112 set up in someother way such that an energy supply is not interrupted during theentire operation of the network nodes 112. The time synchronization withUTC can be effected as early as during production for example in thecase of such network nodes 112, in particular in the case ofbattery-backed modules. In general, however, modules which, by way ofexample, are not supplied with energy until they are started up (forexample a glucose sensor module supplied with energy from thesurrounding glucose or by means of a temperature gradient) aresynchronized with the UTC only upon contact with the externalcommunicator 126 and an external RTC.

From the knowledge of the corresponding network nodes 112 or modules,the individual network nodes can also establish rules for the normalcase. This creation of rules is designated symbolically by the referencenumeral 332 in FIGS. 3 and 4. This can also involve the establishment ofa new rule. By way of the external communicator 126, by way of example,the rules can be compared with rules established in a superordinatefashion. In this case, by way of example, a check for a collision can beeffected, which is designated symbolically by the reference numeral 334in FIG. 3. This check can be carried out by means of a plausibilityconsideration, by way of example. The module rules can be modified andcoordinated with those of other modules or network nodes 112, forexample by means of corresponding forwarding to the module/systemmanagement 326.

The creation of the rules 332 in the rule generator can be effected invarious ways. The rules can first of all relate to the functionality ofthe entire network 110 or to parts of the network 110, for example dataevaluation. In this way, it is possible, by way of example, to createrules for the data evaluation which are based on the interaction ofitems of information and/or functions of a plurality of network nodes112, such that new functions for the entire network 112 or parts thereofcan arise from this interaction of the network nodes 112. Furthermore,the creation of the rules in method step 332 can also relate to thesystem organization of the network 110. Determined or adaptive formationlaws can generally be used during the rule creation 332.

Further, a fault identification 336 can be effected for example byinterrogation of whether predetermined rules, conventions, thresholds orthe like are contravened. If, by way of example, patterns of behaviourdeviate greatly from the present rules, then failsafe measures can beinitiated depending on the definition of the discrimination thresholds,by way of example. Accordingly, the method can comprise for example atleast one monitoring step, designated symbolically by the referencenumeral 338 in FIG. 3. The fault identification 336 and the check for acollision 334 can be part of said monitoring step 338, by way ofexample. The assessment 316 and/or the rule creation 332 can also beincorporated wholly or partly into the monitoring step 338. The failsafemeasures can be configured as a fault routine, for example, and cancomprise for example a corresponding message, a shutdown, a temporaryshutdown or the like. The failsafe rules and the discriminationthresholds either can be defined or can moreover be dynamically adapteddepending on empirical values or else be adapted after interrogationand/or confirmation and/or evaluation of a defined entity.

A rule modification should preferably be checked and confirmed by adefined entity prior to implementation. This can also be part of themonitoring step 338. By way of example, during initialization of anetwork or incorporation of individual network nodes 112 into thenetwork 110, an interactive phase with an expert, for example aphysician, could be carried out in such a way that, by way of example,on account of detected data, the module to be initiated or the networknode 112 to be initiated presents rule proposals or modificationproposals, which can then be confirmed and/or modified by an expert. Thenetwork 110 can in turn derive rules from the interactive process andthus adapt the process iteratively, taking account of oscillationstability criteria.

The self-organization step 218 can furthermore imply a change in therole distribution. By way of example, tasks of individual or a pluralityof network nodes 112 or modules can be permanently or temporarilytransferred to other modules or network nodes. This can be effected, forexample, if computational capacities and/or storage capacities no longersuffice. Thus, by way of example, module controllers can mutuallysupport one another as required, for example in the context of amulticore system. Memory space can also be managed jointly, for example,and scarcely sufficient local memory of individual network nodes 112 canthus be extended. By way of example, such actions are communicated tothe master 134 or preferably coordinated exclusively by the latter.

In order to optimize interoperability, it is possible to establish astandard set of rules and commands for the network 110 and/or individualor a plurality of network nodes 112. These can be agreed uniformly, e.g.nationally and/or internationally, among manufacturers, for example,such that modules or network nodes 112 from different manufacturers canalso be used in the network 110.

Thus, embodiments of the method for generating a medical network aredisclosed. One skilled in the art will appreciate that the teachings canbe practiced with embodiments other than those disclosed. The disclosedembodiments are presented for purposes of illustration and notlimitation, and the invention is only limited by the claims that follow.

What is claimed is:
 1. A method for setting up a medical network forcarrying out at least one medical function with the medical networkincluding at least two network nodes set up for communicating with oneanother, comprising: at least one initialization step, wherein at leasttwo network nodes exchange at least one item of initializationinformation in the initialization step, wherein the initializationinformation includes at least one item of information characterizing thenetwork nodes; at least one self-organization step, wherein the networknodes define a role distribution of the network nodes; at least one workstep, wherein the network carries out the at least one medical functionin the work step, wherein at least two of the network nodes interact inaccordance with the role distribution defined in the self-organizationstep, wherein in the self-organization step at least two of the networknodes define the role distribution of the medical network and theself-organization step is carried out in such a way that the roledistribution comprises a determination of at least one network node asmaster node and a determination of at least one network node as slavenode, and wherein the network node having the most time-criticalfunction is defined as the master node.
 2. The method as in claim 1,wherein the role distribution is defined by making use of the at leastone item characterizing the network nodes.
 3. The method as in claim 2,further comprising a comparison of the at least one item of informationcharacterizing the network nodes, wherein the definition of the roledistribution of network nodes at least partly is based on a result ofthis comparison.
 4. The method as in claim 1, wherein the network nodehaving the most powerful hardware resources is defined as the masternode.
 5. The method as in claim 1, wherein at least two network nodesare capable of taking over the role of the master node.
 6. The method asin claim 1, wherein the role distribution relates to at least one of, adivision of resources; a reciprocal control; a communication among onethe network nodes; a communication with at least one element outside themedical network.
 7. The method as in claim 1, wherein the method isadapted to change the role distribution of the network nodes duringoperation of the medical network.
 8. The method as in claim 1, whereinin the medical function of the network comprises at least one of thefollowing functions, a sensor function for detecting at least onemeasurement variable of a body of a user; or an actuator function forexerting at least one effect on a body of a user.
 9. The method as inclaim 8, wherein the variable of a body of a user is a diagnosticfunction and the effect on the body of the user is a medicationfunction.
 10. The method as in claim 1, wherein at least one of thenetwork nodes is set up for carrying out at least one of the followingnode functions, a sensor function; an actuator function; a communicationfunction for exchanging items of information with at least one elementnot assigned to the network; a communication function for exchangingitems of information with at least one user; a data processing function;a data storage function; an energy obtaining function for generatingenergy from an environment of the network node; or a clock function forproviding a real time.
 11. The method as in claim 1, wherein at leasttwo of the network nodes are set up for communicating with one anothervia a body of a user as signal transmission medium.
 12. The method as inclaim 1, wherein, in the initialization step, at least one network nodewhich is to be newly inserted into the network is physically assigned tothe network, wherein the network node which is to be newly insertedexchanges the initialization information with at least one network nodealready present in the network.
 13. The method as in claim 12, whereinthe initialization information comprises at least one of the followingitems of information, an item of information about a type of one of thenetwork nodes; an item of information about a function of one of thenetwork nodes; an item of information about a configuration of hardwareresources of one of the network nodes; an item of information about acommunication protocol of one of the network nodes; an information abouta pre-configuration.
 14. The method as in claim 13, wherein the item ofinformation about a type of one of the network nodes is a medicalfunction; the item of information about a configuration of hardwareresources of one of the network nodes is a data storage device or a dataprocessing device of a network node; and, the information about apre-configuration is an information on a calibration or a mathematicalset-up.
 15. The method as in claim 1, wherein the self-organization stepis carried out in such a way that the role distribution comprises aninteraction of at least two network nodes for carrying out at least onefunction which cannot be achieved individually by the network nodes. 16.The method as in claim 15, wherein the self-organization step is carriedout in such a way that the role distribution comprises a dynamicallyadaptable set of role distributions.
 17. The method as in claim 15,wherein the self-organization step is carried out in such a way that therole distribution comprises a utilization of at least one resource of afirst network node by at least one second network node.
 18. The methodas in claim 15, wherein, in the self-organization step, at least oneitem of information about the role distribution is stored in at leastone data storage device of at least one of the network nodes.
 19. Themethod as in claim 18, wherein the data storage device is data storagedevices in a plurality of network nodes.
 20. The method as in claim 15,wherein the self-organization step is controlled by one of thefollowing, a pre-definition of boundary conditions; or a confirmation ofat least one result of the self-organization step by at least onesuperordinate authority.
 21. The method as in claim 15, furthercomprising at least one log-off step to remove one network node; and,after the log-off step, the self-organization step is carried out againin order to newly define a role distribution of the remaining network.22. The method as in claim 15, wherein a warning is issued to a user if,in the self-organization step, it is identified that a sufficientfunctionality of the remaining network no longer exists.
 23. The methodas in claim 15, wherein at least two of the network nodes are in eachcase set up for performing at least one node function, and wherein theself-organization step and the work step are carried out in such a waythat the function of the network comprises at least one further functiongoing beyond the sum of the node functions.
 24. The method as in claim1, wherein the at least one further function comprises at least one ofthe following functions, provision of an item of information, whereinthe information is generated by combination of at least two measurementvariables of at least two network nodes; driving of at least one firstnetwork node by at least one second network node; a control function,wherein at least one first network node with an actuator function issubjected to open-loop and/or closed-loop control by the comparison ofat least one measurement value of at least one second network node witha measurement function with at least one desired value.
 25. The methodas in claim 1, further comprising at least one monitoring step, whereinthe monitoring step is set up for monitoring at least one result of theself-organization step or of the work step and for carrying out at leastone fault routine upon identification of a standard deviation.